Methods for creating a compound library and identifying lead chemical templates and ligands for target molecules

ABSTRACT

A method for developing a library of compounds, the compound library, a method for identifying ligands for target molecules, and a method for identifying lead chemical templates, which, for example, can be used in drug discovery and design are provided. Certain embodiments of these methods include the use of NMR spectroscopy.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a divisional of U.S. patent application Ser.No. 09/677,107, filed on Sep. 29, 2000, issued as U.S. Pat. No.6,677,160, which claims priority to U.S. Provisional Application Ser.Nos. 60/156,818, filed on Sep. 29, 1999, 60/161,682, filed on Oct. 26,1999, and 60/192,685, filed on Mar. 28, 2000, which are incorporatedherein by reference.

BACKGROUND OF THE INVENTION

From an organic chemistry standpoint, the process of drug design can beconsidered to involve two steps. First, a lead chemical template (oftenone or more) is selected. Second, a synthetic chemistry effort isundertaken to create analogs of the lead chemical template to create acompound or compounds possessing the desired therapeutic andpharmacokinetic properties.

An important step in the drug discovery process is the selection of asuitable lead chemical template upon which to base a chemistry analogprogram. The process of identifying a lead chemical template for a givenmolecular target typically involves screening a large number ofcompounds (often more than 100,000) in a functional assay, selecting asubset based on some arbitrary activity threshold for testing in asecondary assay to confirm activity, and then assessing the remainingactive compounds for suitability of chemical elaboration.

This process can be quite time- and resource-consuming, and has numerousdisadvantages. It requires the development and implementation of ahigh-throughput functional assay, which by definition requires that thefunction of the molecular target be known. It requires the testing oflarge numbers of compounds, the vast majority of which will be inactivefor a given molecular target. It leads to the depletion of chemicalresources and requires the continual maintenance of large collections ofcompounds. Importantly, it often leads to a final pool of potential leadtemplates that for the most part, with the exception of affinity for agiven molecular target, do not possess desirable drug-like qualities. Insome cases, high-throughput functional assays do not identify anycompounds from the large number (e.g., 100,000) of compounds screenedthat meet the criteria established for activity.

Thus, what is needed is a faster and better approach to identifying alead chemical template.

SUMMARY OF THE INVENTION

The present invention is related to rational drug design. Specifically,the present invention provides an approach to the development of alibrary of compounds as well as methods for identifying compounds (e.g.,ligands) that bind to a specific target molecule (e.g., proteins) andlead chemical templates that can be used, for example, in drug discoveryand design. Significantly and preferably, this approach for identifyingligands for target molecules (e.g., proteins) uses nuclear magneticresonance (NMR) spectroscopy. There are numerous NMR spectroscopictechniques currently available that detect binding of small molecules totargets such as protein targets, including targets identified usinggenomics techniques that lack a functional assay. Ligands with onlymoderate binding affinities, which might be overlooked in a traditionalfunctional assay but yet might serve as templates for subsequentsynthetic chemistry efforts, can potentially be identified using thepresent invention. Preferably, one method of the present inventioninvolves the use of flow NMR techniques, which can reduce the amount oftime and effort required to evaluate small molecules for binding to agiven target.

In one aspect, the present invention provides a method of creating achemical compound library, and the library itself. The method includes:selecting compounds having a molecular weight of no greater than about350 grams/mole; and selecting compounds having a solubility indeuterated water of at least about 1 mM at room temperature. Preferably,a majority (i.e., greater than 50%) of the compounds in the chemicalcompound library have a molecular weight of no greater than about 350grams/mole and a solubility in deuterated water of at least about 1 mMat room temperature. More preferably, at least about 75% of thecompounds, and most preferably, all of the compounds in the chemicalcompound library have a molecular weight of no greater than about 350grams/mole and a solubility in deuterated water of at least about 1 mMat room temperature. Preferably, this library of compounds includes atleast about 75 compounds, more preferably, at least about 300 compounds,and most preferably, at least about 2000 compounds, and have relativelydiverse chemical structures. Herein, the molecular weights of thecompounds are determined without solubilizing counterions (if thecompounds are salts) and without water molecules of hydration. Also,concentrations are reported based on aqueous solutions, which may or maynot include a buffer.

In another embodiment, the present invention provides a method ofidentifying a lead chemical template (of which there often may be one ormore), for example, for designing a bioactive agent such as a drug(e.g., a compound having therapeutic and/or prophylactic capabilities).The method includes: selecting compounds having a molecular weight of nogreater than about 350 grams/mole, and a solubility in deuterated waterof at least about 1 mM at room temperature to create a chemical compoundlibrary; identifying at least one compound from the library thatfunctions as a ligand (i.e., a compound that binds to a target molecule)having a dissociation constant to a target molecule (e.g., protein) ofno weaker than (i.e., at least) about 100 μM; and using the ligand toidentify a lead chemical template, which can be used, for example, fordesigning a drug. Preferably, the lead chemical template has adissociation constant to a target molecule (e.g., protein) of no weakerthan (i.e., at least) about 1 μM. Preferably, the lead chemical templatecan be identified through further screening efforts or through directchemical elaborations. Preferably, a majority (i.e., greater than 50%)of the compounds in the chemical compound library, more preferably, atleast about 75%, and most preferably, all of the compounds in thechemical compound library, have a molecular weight of no greater thanabout 350 grams/mole and a solubility in deuterated water of at leastabout 1 mM at room temperature.

Another embodiment of the present invention provides a method ofidentifying a compound that binds to a target molecule (e.g., protein).The method includes: providing a plurality of mixtures of testcompounds, each mixture being in a (separate) sample reservoir(preferably, a sample reservoir of a multiwell sample holder (e.g., a96-well microtiter plate)); introducing a target molecule (e.g.,protein) into each of the sample reservoirs to provide a plurality oftest samples; providing a nuclear magnetic spectrometer equipped with aflow-injection probe; transferring each test sample from the samplereservoir into the flow-injection probe; collecting a relaxation-edited(preferably, a one-dimensional (1D) relaxation-edited) nuclear magneticresonance spectrum (preferably, a ¹H NMR spectrum) on each sample ineach reservoir; and comparing the spectra of each sample to the spectrataken under the same conditions in the absence of the target molecule(e.g., protein) to identify compounds that bind to the target molecule(e.g., protein); wherein the concentration of target molecule (e.g.,protein) and each compound in each sample is no greater than about 100μM. Preferably, the mixture of compounds comprises at least about 3compounds (more preferably, at least about 6 compounds, and mostpreferably, at least about 10 compounds), each having at least onedistinguishable resonance in an NMR spectrum (preferably, a 1D NMRspectrum, and more preferably, a 1D ¹H NMR spectrum) of the mixture.

Preferably, in this method, the ratio of target molecule (e.g., protein)to compounds in each sample reservoir is about 1:1. More preferably, theconcentration of target molecule (e.g., protein) and each compound ineach sample is at least about 25 μM. Most preferably, the concentrationof target molecule (e.g., protein) and each compound in each sample isno greater than about 50 μM.

Sample requirements can be reduced even further if WaterLOGSY(water-ligand observation with gradient spectroscopy) methods are usedas an alternative to the relaxation-editing method described above todetect the binding interaction.

The present invention provides yet another method of identifying acompound that binds to a target molecule (e.g., protein). This methodincludes: providing a plurality of mixtures of test compounds, eachmixture being in a sample reservoir; introducing a target molecule intoeach of the sample reservoirs to provide a plurality of test samples;providing a nuclear magnetic resonance spectrometer equipped with aflow-injection probe; transferring each test sample from the samplereservoir into the flow-injection probe; collecting a WaterLOGSY nuclearmagnetic resonance spectrum (preferably, a 1D WaterLOGSY nuclearmagnetic resonance spectrum) on each sample in each reservoir; andanalyzing the spectra of each sample to distinguish binding compoundsfrom nonbinding compounds by virtue of the opposite sign of theirwater-ligand nuclear Overhauser effects (NOEs). Preferably, theconcentration of each compound in each sample is no greater than about100 μM, although higher concentrations can be used if desired.

In this method when binding is detected using the WaterLOGSY technique,extremely low levels of target can be used with ratios of ligand totarget of about 100:1 to about 10:1. Preferably, the concentration oftarget molecule is no greater than about 10 μM. More preferably, theconcentration of target molecule is about 1 μM to about 10 μM. For dataanalysis, binding compounds are distinguished from nonbinders (i.e.,nonbinding compounds) by the opposite sign of their water-ligand NOEs.With this method, there is no need to collect a reference spectrum inthe absence of a target molecule.

In preferred embodiments of the present invention, a majority of thecompounds in the library have a solubility in deuterated water of atleast about 1 mM at room temperature (i.e., about 25° C. to about 30°C.), and a molecular weight of no greater than about 350 grams/mole. Foreffective use of a compound identified as a ligand for a given target inthe search for a lead chemical template, preferably, the dissociationconstant of the identified ligand to a target molecule is no weaker than(i.e., at least) about 100 μM. For effective use of a lead chemicaltemplate in further drug design, preferably, the dissociation constantfor the lead chemical template to a target molecule is no weaker than(i.e., at least) about 1 μM.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Schematic diagram illustrating the use of NMR to discover aligand having an approximate dissociation constant of 1.0×10⁻⁴ M (leftfigure), to use the discovered ligand to direct the discovery of a leadchemical template having an approximate dissociation constant of1.0×10⁻⁶ M (middle figure), and then via synthetic chemistry andstructure-directed drug design arrive at a drug candidate having anapproximate dissociation constant of 1.0×10⁻⁸ M.

FIG. 2. Comparison of the two-dimensional HA (hydrogen-bond acceptor)vs. CHRG (charge) BCUT plots for the compounds contained in the NMRlibrary described herein (dark squares) and a larger chemical librarydatabase (gray spots).

FIG. 3A. One-dimensional relaxation-edited ¹H NMR spectrum of a compoundset containing three compounds designated (1), (2), and (3). Resonancesare numbered corresponding to the individual components in the set.

FIG. 3B. One-dimensional relaxation-edited ¹H NMR spectrum of the sameset of compounds shown in FIG. 3A in the presence of flavodoxin. Arrowsidentify resonances that experience a significant reduction inintensity.

FIG. 4A. Region of the 2D ¹H-¹⁵N HSQC spectrum of flavodoxin alone andin the presence of a 10-fold excess of compound (1). Residues withsignificant chemical shift changes in the presence of (1) are boxed andlabeled with their amino acid type and sequence number.

FIG. 4B. Secondary structure representation of the flavodoxin globalfold. The flavin cofactor is shown in stick format. Residues with thelargest chemical shift changes in the presence of (1) are shown inwhite.

FIG. 5A. One-dimensional relaxation-edited ¹H NMR spectrum of a compoundset containing three compounds in the presence of flavodoxin.

FIG. 5B. One-dimensional relaxation-edited ¹H NMR spectrum of the samecompound set shown in FIG. 5A in the presence of the antibacterialtarget protein. Arrows identify resonances from Ligand A (FIG. 6) thatexperience a significant reduction in intensity in the presence of theantibacterial target protein.

FIG. 6. IC₅₀ values of the original ligand, Ligand A, and fourstructurally related compounds, Ligands B-E, identified in a similaritysearch based on the structure of Ligand A.

FIG. 7. Region of the 2D ¹H-¹⁵N HSQC spectrum of the antibacterialtarget protein alone and in the presence of a 10-fold excess of LigandA. Several resonances with large chemical shift changes in the presenceof Ligand A are boxed and labeled with their amino acid sequence number.

FIG. 8A. One-dimensional relaxation-edited ¹H NMR spectrum of a compoundset containing ten compounds.

FIG. 8B. One-dimensional relaxation-edited ¹H NMR spectrum of the sameset of compounds in FIG. 8A in the presence of the antiviral targetprotein. Arrows identify resonances, all belonging to the same compound,that experience a significant reduction in intensity in the presence ofthe antiviral target protein.

FIG. 9. Region of the 2D ¹H-¹⁵N HSQC spectrum of the antiviral targetprotein alone and in the presence of the ligand identified from FIG. 8.Several resonances with large chemical shift changes in the presence ofthis ligand are boxed and labeled with their amino acid sequence number.

FIG. 10. Schematic of the BEST flow system: (1) computer workstation,(2) NMR console, (3) Gilson sample handler, (4) flow probe in themagnet, and (5) nitrogen gas. The Gilson sample handler is labeled asfollows: (A) keypad, (B) syringe, (C) injector, (D) solvent reservoir,(E) solvent rack, (F) sample racks, (G) waste reservoir, (H) Rheodynevalves, (D) injection port, and (J) recovery unit.

FIG. 11. Schematic of a Bruker flow probe showing (A) the total probevolume, (B) the flow cell volume, and (C) the positioning volume.

FIG. 12. 600.13 MHz ¹H NMR spectra of a 100 μM NMR library sample withthe positioning volume set to (A)−100 μl, (B) 0 μl, and (C)+100 μl.

FIG. 13. Overlay of the two-dimensional HA (hydrogen-bond acceptor) vs.CHRG (charge) BCUT plots for the compounds in the CMC index (gray) andthe lead-like compounds contained therein (black).

FIG. 14. Regions of the 600.13 MHz relaxation-edited ¹H NMR spectra of anine compound mixture (A) without and (B) with added target protein.Protein and each ligand were 50 μM. Spectra were acquired on a Bruker 5mm flow-injection probe at 27° C. A total of 1K scans were collectedresulting in a total acquisition time of about 60 minutes per spectrum.A relaxation filter of 174 milliseconds (ms) was used. Arrows identifyresonances that disappear in the presence of protein.

FIG. 15. Regions of the 600.13 MHz relaxation-edited ¹H NMR spectra of asingle compound (A) without and (B) with added target protein. Proteinand ligand were 50 μM. Spectra were acquired on a regular Bruker 5 mmTXI probe at 27° C. A total of 512 scans were collected resulting in atotal acquisition time of about 30 minutes per spectrum. A relaxationfilter of 174 ms was used.

FIG. 16. Region of the 600.13 MHz WaterLOGSY spectrum of a compoundmixture with added target protein. The concentration of protein was 10μM while the concentration of each compound was 100 μM. The spectrum wasacquired on a Bruker 5 mm flow-injection probe at 27° C. A total of 4Kscans were collected resulting in a total acquisition time of about 288minutes. A mixing time of 2.0 seconds was used.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS OF THE INVENTION

The present invention involves the selection of a generally smalllibrary of structurally diverse compounds that are generally watersoluble, have a relatively low molecular weight, and are amenable tosynthetic chemistry elaboration. Significantly and advantageously, forcertain embodiments, the present invention preferably involves carryingout a binding assay at relatively low concentrations of target and nearequimolar ratios of ligand to target, or even at extremely lowconcentrations of target and higher ratios of ligand to target.

In a method of the present invention, a relatively small subset ofcompounds (preferably, at least about 75, more preferably, at leastabout 300, most preferably, at least about 2000, and typically no morethan about 10,000) that mimics the structural diversity of compounds inmuch larger collections is created based on a predetermined set ofcriteria. This generally small library is screened for binding affinityto a target molecule (as determined herein by dissociation constants).The compounds from the library that are identified to be effectiveligands (typically, having an affinity for a desired target as evidencedby a dissociation constant of at least about 1.0×10⁻⁴ M) are then usedto focus further screening efforts or to direct chemical elaborations toarrive at one or more lead chemical templates (which, typically have anaffinity for a desired target as evidenced by a dissociation constant ofat least about 1.0×10⁻⁶ M). This process is shown schematically in FIG.1.

Significantly, time and resources are saved by screening far fewercompounds using the present invention. Use of a binding assay, such asthe one based on NMR spectroscopy described herein, eliminates the needto develop a high-throughput functional assay, and also allows themethods to be used on molecular targets lacking a known function.

Thus, the present invention provides methods of identifying a compoundthat binds to a target molecule (preferably, a protein) that are basedon NMR spectroscopy techniques. Such methods typically involve the useof relaxation-editing techniques, for example, which involve monitoringchanges in resonance intensities (preferably, significant reductions inintensities) of the test compound upon the addition of a targetmolecule. Preferably, the relaxation-editing techniques areone-dimensional, and more preferably, one-dimensional ¹H NMR techniques.Alternatively, such methods can involve the use of WaterLOGSY. Thisinvolves the transfer of magnetization from bulk water to detect thebinding interaction. Using WaterLOGSY techniques, binding compounds aredistinguished from nonbinders by the opposite sign of their water-ligandnuclear Overhauser effects (NOEs).

Important elements that contribute to the success of the methods of theinvention preferably include developing a suitable small library ofcompounds to screen, carrying out the binding assay at lowconcentrations of target and near equimolar ratios of ligand to target(for relaxation-editing), or at extremely low concentrations of target(if desired) and higher ratios of ligand to target (for WaterLOGSY), andthe capacity for rapid throughput of data collection. For example, forrelaxation-editing NMR techniques, the concentration of target moleculeis preferably no greater than about 1.0×10⁻⁴ M, and for WaterLOGSY NMRtechniques, the concentration of target molecule is preferably nogreater than about 10 μM.

The selection of compounds in a small library (preferably, at leastabout 75 compounds, more preferably, at least about 300 compounds, andmost preferably, at least about 2000 compounds) is important in that itsdiversity should mimic the diversity of larger compound collections.Preferably, each component possesses many of the desirable qualities ofa lead chemical template. These include water solubility, low molecularweight (preferably, no greater than about 350 grams/mole, morepreferably, no greater than about 325 grams/mole, and most preferably,less than about 325 grams/mole), and amenability to synthetic chemistryelaboration. Templates possessing these qualities, as compared to atemplate selected randomly, are preferably considered to be predisposedto being lead-like and having an increased likelihood of ultimatelyleading to a drug.

Good structural diversity in a library increases the likelihood that oneor more compounds will possess structural characteristics important forbinding to a given molecular target. Predisposing the compounds to bewater soluble, to have low molecular weight (preferably, no greater thanabout 350 grams/mole, more preferably, no greater than about 325grams/mole, and most preferably, less than about 325 grams/mole), and tobe amenable to synthetic elaboration increases the likelihood that acompound found to be a ligand will lead to a related compound orcompounds suitable as a lead chemical template for use, for example, ina process of identifying an effective therapuetic and/or prophylacticagent. Additionally, the requirement for good water solubility(preferably, at least about 1.0×10⁻³ M in deuterated water at roomtemperature) is important in that it increases the likelihood of successof other downstream drug-design projects, such as co-crystallizationattempts, calorimetry studies, and enzyme kinetic analyses.

Carrying out a relaxation-editing binding assay (preferably, a 1D ¹H NMRassay) at low concentrations of target (preferably, no greater thanabout 1.0×10⁻⁴ M, and more preferably, no greater than about 5.0×10⁻⁵ M)and near equimolar ratios of ligand to target creates the requirementthat compounds testing positive for binding have affinities within afactor of about 3-4 of this same concentration (preferably, having adissociation constant of no less than about 2.0×10⁻⁴ M). A similaraffinity threshold can be obtained by carrying out a WaterLOGSY basedbinding assay at even lower target concentrations (preferably, nogreater than about 10 μM, but is more preferably about 1 μM to about 10μM) and ligand to target ratios of about 100:1 to about 10:1. This levelof affinity is desired if the subsequent steps of focused screening anddirected chemical elaboration are to be successful in elucidating a leadchemical template with very low affinity (e.g., one having adissociation constant of at least about 1.0×10⁻⁶ M). Carrying out theinitial screening at these low concentrations also avoids detection ofunwanted compounds with much smaller dissociation constants in the1.0×10⁻³ M range, which are less specific in their binding and thereforeharder to turn into lead chemical templates given their weak affinityinitially.

The capacity for rapid throughput of data collection is important if alarge number of molecular targets are to be screened. Preferably, flowNMR techniques can reduce the amount of time and effort required toevaluate small molecules for binding to a given target. For example, theuse of a Bruker Efficient Sample Transfer system in combination with atubeless, flow-injection NMR probe has proven to be much faster and lesslabor intensive than the use of traditional NMR tubes. A significantincrease in throughput is obtained compared to both manual samplechanging and to using an autosampler. Implementation of the screeningprocess using multiwell sample holders also standardizes theexperimental setup as well as the components in a given mixture from onemolecular target to the next.

The following is a description of a preferred method for carrying outthe present invention. It is provided for exemplification purposes onlyand should not be considered to unnecessarily limit the invention as setforth in the claims.

In the design of a preferred small library of structurally diversecompounds according to the present invention, compounds were selectedfrom a large library based on dissimilarity, predicted water solubility,low molecular weight, and chemical intuition. Some were based onframeworks suggested in the literature, although someliterature-suggested frameworks were consciously avoided. Each compoundwas tested for solubility at 1.0×10⁻³ M in ²H₂O and for purity by massspectrometry and ¹H NMR spectroscopy. Compounds deemed to be watersoluble and pure were kept for inclusion in the final library(approximately 30% of the initial compounds). The resulting librarycontains approximately 300 compounds. One measure of the degree ofstructural diversity of the compounds in this small library is shown inFIG. 2. This is based on the technique described in Pearlman et al.,Perspectives in Drug Discovery & Design, 9, 339-353 (1998). Preferably,the compound library includes compounds of sufficiently diverse chemicalstructure that one would expect at least one compound to bind to a giventarget protein with an affinity (dissociation constant) no weaker than(i.e., at least) about 200 μM. Herein, compounds of diverse chemicalstructure are those that have a variety of backbone hydrocarbonstructures (e.g., linear, branched, cyclic—which may or may not bearomatic, have fused rings, etc.), optionally including a variety ofheteroatoms (e.g., oxygen, nitrogen) and a variety of functional groups(e.g., carbonyls) in a variety of positions (e.g., pointing in variousdirections at a variety of distances from each other). Ideally, usingthe technique described in Pearlman et al., Perspectives in DrugDiscovery & Design, 9, 339-353 (1998), the library of compounds displaysa pattern of well-dispersed black squares (e.g., see FIG. 2).

In order to increase the throughput of the NMR screening, compounds weregrouped into 32 sets of 6-10 compounds that have at least onedistinguishable resonance in a 1D ¹H NMR spectrum of the mixture. Toaccomplish this, a 1D ¹H NMR spectrum was obtained of each mixture in100% ²H₂O and in 0.1 M sodium phosphate/100% ²H₂O at pH 6.5. Twosolvents were used in order to determine the assignment of pH-titratableresonances in the spectrum. Each of the 32 mixtures was then plated outinto separate wells of a 96-well plate, using 25 μL of a 1.0×10⁻³ Msolution, and frozen at −80° C. until needed. In an initial version ofthe NMR screening library, approximately 70 compounds were grouped into21 sets of 3-4 compounds each.

After a 96-well plate had completely thawed, a solution containing amolecular target protein was added to each well containing a mixture ofcompounds in the 96-well plate. The final concentration of protein istypically about 5.0×10⁻⁵ M. The ratio of each compound in a mixture toprotein is typically about 1:1. This process typically involves adding475 mL of protein to each mixture. Dispersion throughout the mixture wasfacilitated by shaking the 96-well plate for 20 minutes followingaddition of protein.

A 1D relaxation-edited ¹H NMR spectrum was collected on eachprotein/compound mixture solution using a Bruker DRX600 or a BrukerAMX400 spectrometer equipped with a shielded magnet, a Gilson samplehandler, and a 5 mm (250 μL sample cell) flow-injection NMR probe. Theuse of a shielded magnet greatly reduces the magnetic fringe fieldsurrounding the high field magnet and allows the Gilson sample handlerto be placed in close proximity to the magnet. The Gilson liquid samplehandler transfers samples from 96-well plates into the flow-injectionprobe and, if desired, returns the samples back to the 96-well plate. Acompound or compounds that bind to a given target are identified bycomparing the 1D relaxation-edited ¹H NMR spectrum collected in thepresence of added protein to that of the identical mixture of compoundsin the absence of protein. A compound is identified as a ligand for agiven target if one or more of its resonances (preferably ¹H resonanceor resonances) are significantly reduced (i.e., greater than about 75%reduction in one or more resonances) in intensity in the presence oftarget molecule (e.g., protein) as compared to the spectrum collected inan identical fashion in the absence of target molecule (e.g., protein).

Sample requirements can be reduced even further if WaterLOGSY methodsare used as an alternative to the relaxation-editing method describedabove to detect the binding interaction. WaterLOGSY is described in moredetail in C. Dalvit et al., J. Biomol. NMR, 18, 65-68 (2000).

Since the WaterLOGSY experiment relies on the transfer of magnetizationfrom bulk water to detect the binding interaction, it is a verysensitive technique. As such, the concentration of target molecule(e.g., protein) in each sample preferably can be reduced to no greaterthan about 10 μM (preferably, about 1 μM to about 10 μM) while theconcentration of each compound can be about 100 μM. This results inratios of test compound to target molecule in each sample reservoir ofabout 100:1 to about 10:1. The exact concentrations and ratios used canvary depending on the size of the target molecule, the amount of targetmolecule available, the desired binding affinity detection limit, andthe desired speed of data collection. In contrast to therelaxation-editing method, there is no need to collect a comparison orcontrol spectrum to identify binding compounds from nonbinders. Instead,binding compounds are distinguished from nonbinders by the opposite signof their water-ligand nuclear Overhauser effects (NOEs).

Ligand binding was confirmed by making fresh solutions containing onlythe identified ligand, with and without added protein at a 1:1 ratio,and comparing the 1D relaxation-edited ¹H NMR spectra. In addition, theligand's dissociation constant was estimated by analyzing several 1Ddiffusion-edited ¹H NMR spectra collected at several gradient strengths.The relative diffusion coefficients for the protein, for the ligand inthe presence of protein, and for the ligand in the absence of protein,in conjunction with known protein and ligand concentrations, were usedto estimate the ligand's dissociation constant. These spectra aretypically collected using an NMR spectrometer, a conventional highresolution probe, and regular 5 mm NMR tubes.

Once a ligand had been identified and confirmed, its structure is usedto identify available compounds with similar structures to be assayedfor activity or affinity, or to direct the synthesis of structurallyrelated compounds to be assayed for activity or affinity. Thesecompounds are then either obtained from inventory or synthesized. Mostoften, they are then assayed for activity using enzyme assays. In thecase of molecular targets that are not enzymes or that do not have anenzyme assay available, these compounds can be assayed for affinityusing NMR techniques similar to those described above, or by otherphysical methods such as isothermal denaturation calorimetry. Compoundsidentified in this step with affinities for the molecular target ofabout 1.0×10⁻⁶ M are typically considered lead chemical templates.

In some instances, ligand binding is further studied using more complexNMR experiments or other physical methods such as calorimetry or X-raycrystallography. These downstream studies have a greater chance ofsuccess since the ligands and lead chemical templates so identified arefairly water soluble. For instance, if [¹⁵N]protein is available, 2D¹H-¹⁵N HSQC (heteronuclear single quantum correlation) spectra can becollected with and without added ligand to locate the ligand's bindingsite on the protein. In cases where the protein is small enough(molecular weight less than about 30,000) and further characterizationof protein/ligand interactions is desired, 3D NMR experiments can becarried out on [¹³C/¹⁵N]protein/[¹²C/¹⁴N]ligand complexes. Attempts tosoak lead chemical templates identified by this method into existingprotein crystals, or to form co-crystals, can also be carried out.

EXAMPLES

Objects and advantages of this invention are further illustrated by thefollowing examples, but the particular materials and amounts thereofrecited in these examples, as well as other conditions and details,should not be construed to unduly limit this invention.

Example 1 Use of NMR Spectroscopy to Identify Ligands for Flavod xin

Reference 1D ¹H NMR spectra of the individual compounds and combinationsof compounds were recorded in ²H₂O solution on a Bruker ARX-400spectrometer. One-dimensional relaxation-edited ¹H NMR spectra ofsamples containing a mixture of flavodoxin and a given compoundcombination were recorded in ²H₂O solution on a Bruker DRX-500spectrometer. A spin lock time of 350 milliseconds was used. Thescreening experiments were carried out on solutions that were 5.0×10⁻⁵ Mflavodoxin and 1.0×10⁻⁴ M of each ligand present. Two-dimensional ¹H-¹⁵NHSQC spectra were recorded in ¹H₂O solution on a Bruker DRX-500spectrometer. Samples were 5.0×10⁻⁵ M flavodoxin with a 3-10 fold excessof a given ligand. All solutions containing flavodoxin were bufferedwith 1.0×10⁻² M phosphate at pH 6.4. The Desulfovibrio vulgarisflavodoxin used in all experiments was ¹⁵N-enriched.

To create the NMR ligand screening library, an initial set of compoundswas selected by a search of a larger library of compounds based ondissimilarity, predicted water solubility, low molecular weight(preferably, no greater than about 350 grams/mole, more preferably, nogreater than about 325 grams/mole, and most preferably, less than about325 grams/mole), and chemical intuition. These compounds were thentested for water solubility and purity. Compounds with no visibleprecipitate or suspension at a concentration of 1.0×10⁻³ M were deemedto be water soluble. Compounds with the predicted parent ion molecularweight and otherwise normal mass spectra were deemed to be pure.Reference 1D ¹H NMR spectra were collected on compounds meeting thesecriteria. Combinations of three or four compounds were then assembled inwhich at least one distinguishing ¹H NMR resonance for each compoundcould be readily identified. A reference 1D ¹H NMR spectrum was thenrecorded for each combination of compounds. As an example, threecompounds, designated here as (1), (2), and (3), were combined into oneset. The 1D ¹H NMR spectrum of this combination set is illustrated inFIG. 3A. Resonances from each of the individual components are readilyidentified, especially in the aliphatic region of the spectrum. At thetime of this work, the NMR ligand library contained approximately 70compounds incorporated into 21 unique assortments containing three orfour compounds each.

One-dimensional relaxation-edited ¹H NMR spectroscopy was used to screenthe library for binding to the model target protein, Desulfovibriovulgaris flavodoxin. For most of the compound combinations in thepresence of flavodoxin, there was little or no reduction in resonanceintensity with the 350-millisecond spin-lock time. However, for two ofthe compound combinations, the intensities of resonances correspondingto one of the compounds in the mixture were significantly reduced. FIG.3B exemplifies this for the same combination illustrated in FIG. 3A. Theresonances corresponding to (2) and (3) are not affected by thespin-lock filter in the presence of flavodoxin. However, the twoaliphatic resonances of (1) at 1.8 ppm and 3.7 ppm are significantlyreduced in intensity by the spin-lock filter in the presence offlavodoxin, indicating that (1) is binding to the protein. Similarexperiments indicated that a second compound, contained within adifferent combination of compounds, also binds to flavodoxin. These werethe only two compounds among those tested that clearly bind toflavodoxin.

Two-dimensional ¹H-¹⁵N HSQC spectra were subsequently recorded on[¹⁵N]flavodoxin to further investigate the interaction of these twoligands with the protein. Since amide backbone ¹H and ¹⁵N resonanceassignments for this protein are known (Stockman et al., J. Biomol. NMR,3, 133-149 (1993)), analysis of the ligand-induced changes in ¹H and ¹⁵Nchemical shifts could be used to identify the ligand binding sites.Typical chemical shift changes observed are delineated in FIG. 4A, whichshows an overlay of the ¹H-¹⁵N HSQC spectra of flavodoxin alone and inthe presence of excess (1). Residues with the largest ligand-inducedchemical shift changes are indicated in white on the structure of theprotein (Watt et al., J. Mol. Biol., 218, 195-208 (1991)) in FIG. 4B.Compound (1) binds near the flavin cofactor binding site. Interestingly,the binding sites as defined by this data for the two ligands identifiedare at adjacent, partially overlapping locations on the surface near theflavin cofactor binding site.

Example 2 Use of NMR Spectroscopy to Identify a Lead Chemical Templatefor an Antibacterial Target Protein

Numerous protein targets are amenable to an NMR process of identifying alead chemical template. In this example, the technique is illustratedfor an antibacterial target protein with a molecular weight of about 20kDa.

All solutions containing the antibacterial target protein were bufferedwith 2.5×10⁻² M phosphate at pH 7.4. The protein used for the 1Dscreening and dissociation constant determination experiments wasunlabeled, while that used for the 2D ¹H-¹⁵N HSQC experiments was¹⁵N-enriched.

One-dimensional relaxation-edited ¹H NMR spectra of samples containing amixture of the target protein and a given compound combination wererecorded in ²H₂O solution on a Bruker DRX-500 spectrometer. A spin locktime of 350 milliseconds was used. The screening experiments werecarried out on solutions that were 1.0×10⁻⁴ M target protein and1.0×10⁻⁴ M of each ligand. The library used for the screening processwas identical to that described in Example 1.

Two-dimensional ¹H-¹⁵N HSQC spectra were recorded in ¹H₂O solution on aBruker DRX-500 spectrometer. Samples contained 8.0×10⁻⁵ M target proteinwith a 9-10 fold excess of a given ligand.

Ligand dissociation constants were estimated by determining relativediffusion coefficients for target protein alone, ligand in the absenceof target protein, and ligand in the presence of target protein (Lennonet al., Biophys. J., 67, 2096-2109 (1994)). Relative diffusioncoefficients were determined using pulsed-field-gradient NMR experimentsincorporating a bipolar longitudinal eddy-current delay sequence (Wu, J.Magn. Reson. Ser. A, 115, 260-264 (1995)).

One-dimensional relaxation-edited ¹H NMR spectroscopy was used to screenthe small molecule library for binding to this target protein in amanner analogous to that previously described in Example 1. With thistechnique, a reduction in resonance intensity is observed if a compoundinteracts with the target protein, thus identifying it as a ligand. Formost of the compound combinations in the presence of the antibacterialtarget protein, there was little or no reduction in resonance intensitywith the 350-millisecond spin-lock time. However, for some of thecompound combinations, the intensities of resonances corresponding toone of the compounds in the mixture were significantly reduced. Theresults from one such compound combination are described here.

As a control, the 1D relaxation-edited ¹H NMR spectrum of a certainmixture in the presence of a different protein, flavodoxin, is shown inFIG. 5A. All ligand resonances are observed with full intensity. Thecorresponding 1D relaxation-edited ¹H NMR spectrum of this same mixtureacquired in the presence of the antibacterial target protein is shown inFIG. 5B. The intensities of all resonances corresponding to Ligand A inFIG. 5B are clearly reduced in the presence of the antibacterial targetprotein. This indicates that Ligand A is binding to the protein. Thebinding is specific to the antibacterial target protein since theresonance intensities are not reduced in the presence of flavodoxin.

Binding of Ligand A was confirmed by repeating the relaxation-filteredexperiments on a solution containing protein and just Ligand A. Usingthis same sample, as well as samples of protein alone and Ligand Aalone, a separate set of experiments that use pulsed-field-gradienttechniques was collected to determine relative diffusion coefficients.From this data, the dissociation constant for Ligand A was estimated byNMR measurements to be approximately 1.4×10⁻⁴ M.

In order to ascertain whether the binding of Ligand A and structurallyrelated analogs inhibited the activity of this enzyme, and if so to whatdegree, IC₅₀ values were determined. To determine IC₅₀ values, variousconcentrations of selected compounds, originally prepared at 1.0×10⁻² Min 100% DMSO, were titered out to provide at least 12 individualconcentrations. Twenty five (25) μL of each solution (15% DMSO maximum)were added to wells in a 96-well plate, followed by 100 microliters (μL)of a cocktail containing 100 nanograms (ng) of target protein at pH 7.0.Finally, 25 μL of substrate solution was added and the plate (Immulon 2,Dynex) was read in 15 second intervals at 405 nanometers (nm) on aSpectramax 250 plate reader. IC₅₀ profiles and values were generatedusing the program Softmax.

Ligand A was shown to inhibit this enzyme with an IC₅₀ value ofapproximately 9.0×10⁻⁵ M. Subsequently, a similarity search resulted inthe testing of about 10 structurally related compounds for enzymeinhibition. As shown in FIG. 6, four of these compounds had IC₅₀ valuesbetween 2.0×10⁻⁵ M and 1.0×10⁻⁶ M. These very low affinity compounds canserve as lead chemical templates for the design of drugs directedagainst this molecular target.

Two-dimensional ¹H-¹⁵N HSQC spectra were subsequently recorded on[¹⁵N]target protein with and without Ligand A present to furtherinvestigate the interaction of this ligand with the protein. Chemicalshift changes observed in the presence of Ligand A are delineated inFIG. 7, which shows an overlay of the ¹H-¹⁵N HSQC spectra of proteinalone and in the presence of a 10-fold excess of ligand. Residues withthe largest ligand-induced chemical shift changes are boxed.

In this study, a ligand that binds to an antibacterial target proteinwith a dissociation constant of less than about 2.0×10⁻⁴ M wasidentified from a small library of compounds. No prior knowledge of whattypes of ligands ought to bind to this protein was used. The identifiedligand was shown to inhibit this enzyme with an IC₅₀ value ofapproximately 9.0×10⁻⁵ M. Subsequently, a similarity search based on thestructure of this NMR-identified ligand resulted in the testing of about10 structurally related compounds for enzyme inhibition. Four of thesecompounds had IC₅₀ values between about 2.0×10⁻⁵ M and about 1.0×10⁻⁶ M.These very low affinity compounds can serve as lead chemical templatesfor the design of drugs directed against this molecular target. Moreextensive NMR experiments, using isotopically-enriched target protein,concluded that the compounds identified as lead chemical templates do infact bind to the active site of the target protein.

Example 3 Use of NMR Spectroscopy to Identify a Lead Chemical Templatefor an Antiviral Target Protein

Numerous protein targets are amenable to this NMR process of identifyinga lead chemical template. In this example, the technique is illustratedfor an antiviral target protein with a monomer molecular weight ofapproximately 8 kDa that exists as a dimer in solution. This targetprotein was screened using an NMR screening library and flow NMRspectroscopy.

All solutions containing the antiviral target protein were buffered with2.0×10⁻² M phosphate at pH 6.5. The protein used for the 1D screeningand dissociation constant determination experiments was unlabeled, whilethat used for the 2D ¹H-¹⁵N HSQC experiments was ¹⁵N-enriched.

One-dimensional relaxation-edited ¹H NMR spectra of samples containing amixture of the target protein and a given compound combination wererecorded in ²H₂O solution on a Bruker AMX-400 spectrometer. Thespectrometer was equipped with a shielded magnet, a Gilson samplehandler, and a 5 mm (250 μL sample cell) flow-injection NMR probe. Aspin lock time of 350 milliseconds was used. The screening experimentswere carried out on solutions that were 3.8×10⁻⁵ M target protein and5.0×10⁻⁵ M of each ligand. All solutions were contained in a 96-wellplate and were delivered to the 5 mm flow-injection probe using theGilson sample handler. The library used for the screening process wasexpanded from that described in the first two examples. It containedapproximately 300 compounds grouped into 32 separate mixtures.

Two-dimensional ¹H-¹⁵N HSQC spectra were recorded in ¹H₂O solution on aBruker DRX-500 spectrometer. Samples contained 8.3×10⁻⁴ M target proteinalone or in the presence of a given ligand.

Ligand dissociation constants were estimated by determining relativediffusing coefficients for target protein alone, ligand in the absenceof target protein, and ligand in the presence of target protein (Lennonet al., Biophys. J., 67, 2096-2109 (1994)). Relative diffusioncoefficients were determined using pulsed-field-gradient NMR experimentsincorporating a bipolar longitudinal eddy-current delay sequence (Wu, J.Magn. Reson. Ser. A, 115, 260-264 (1995)).

One-dimensional relaxation-edited ¹H NMR spectroscopy was used to screenthe expanded small molecule library for binding to this antiviral targetprotein in a manner analogous to that previously described in the firsttwo examples. With this technique, a reduction in resonance intensity isobserved if a compound interacts with the target protein, thusidentifying it as a ligand. For most of the compound combinations in thepresence of the antiviral target protein, there was little or noreduction in resonance intensity with the 350-millisecond spin-locktime. However, for some of the compound combinations, the intensities ofresonances corresponding to one of the compounds in the mixture weresignificantly reduced. The results from one such compound combinationare described here.

As a control, the 1D relaxation-edited ¹H NMR spectrum of a certainmixture in the absence of protein is shown in FIG. 8A. All resonancesare observed with full intensity. The corresponding 1D relaxation-edited¹H NMR spectrum acquired in the presence of the antiviral target proteinis shown in FIG. 8B. The intensities of all resonances corresponding toa single compound in FIG. 8B are clearly reduced in the presence of theantiviral target protein. This indicates that this compound is bindingto the protein. The binding is specific to the antiviral target proteinsince the resonance intensities are not reduced in the presence of otherprotein targets that have been screened.

In a separate set of experiments that use pulsed-field-gradienttechniques to determine relative diffusion coefficients, thedissociation constant for the identified ligand was estimated by NMRmeasurements to be approximately 40 μM.

Two-dimensional ¹H-¹⁵N HSQC spectra were subsequently recorded on[¹⁵N]target protein with and without the identified ligand present tofurther investigate the interaction of this ligand with the protein.Chemical shift changes observed in the presence of this ligand aredelineated in FIG. 9, which shows an overlay of the ¹H-¹⁵N HSQC spectraof protein alone and in the presence of ligand. Residues with thelargest ligand-induced chemical shift changes are labeled.

Example 4 Screening of Compound Libraries for Protein Binding UsingFlow-Injection NMR Spectroscopy

Introduction

Flow NMR spectroscopy techniques are becoming increasingly utilized indrug discovery and development (B. J. Stockman, Curr. Opin. Drug Disc.Dev., 3, 269-274 (2000)). The technique was first applied to couple theseparation characteristics of liquid chromatography with the analyticalcapabilities of NMR spectroscopy (N. Watanabe et al., Proc. Jpn. Acad.Ser B, 54, 194 (1978)). Since then, HPLC-NMR, or LC-NMR as it is morecommonly referred to, has been broadly applied to natural productsbiochemistry, drug metabolism and drug toxicology studies (J. C. Lindonet al., Prog. NMR Spectr., 29, 1 (1996); J. C. Lindon et al., Drug. Met.Rev., 29, 705 (1997); B. Vogler et al., J. Nat. Prod., 61, 175 (1998);and J.-L. Wolfender et al., Curr. Org. Chem. 2, 575 (1998)). The wealthand complexity of data made available from the latter two applicationshave created the potential for NMR-based metabonomics to complementgenomics and proteomics (J. K. Nicholson et al., Xenobiotica, 29, 1181(1999)). Stopped-flow analysis in LC-NMR, where the chromatographic flowis halted to obtain an NMR spectrum with higher signal-to-noise and thenrestarted when the spectrum has finished collecting, was the forerunnerto the flow-injection systems that will be described here. The largestdifference between the two systems is that one includes a separationcomponent (LC column) and the other does not. The rapid throughputpossible for combinatorial chemistry samples and protein/small moleculemixtures has allowed flow-injection NMR methods to impact medicinalchemistry and protein screening (P. A. Keifer, Drugs Fut., 23, 301(1998); P. A. Keifer, Drug Disc. Today, 2, 468 (1997); P. A. Keifer,Curr. Opin. Biotech., 10, 34 (1999); K. A. Farley et al., SMASH'99,Argonne, Ill., 15-18 Aug. 1999; and A. Ross et al., Biomol. NMR, 16,139(2000)).

Changes in chemical shifts, relaxation properties or diffusioncoefficients that occur upon the interaction between a protein and asmall molecule have been documented for many years (for recent reviewssee M. J. Shapiro et al., Curr. Opin. Drug. Disc. Dev., 2, 396 (1999);J. M. Moore, Biopolymers, 51, 221 (1999); and B. J. Stockman, Prog. NMRSpectr., 33, 109 (1998)). Observables typically used to detect ormonitor the interactions are chemical shift changes for the ligand orisotopically-enriched protein resonances (J. Wang et al., Biochemistry,31, 921 (1992)), or line broadening (D. L. Rabenstein, et al., J. Magn.Reson., 34, 669 (1979); and T. Scherfet al., Biophys. J. ., 64, 754(1993)), change in sign of the NOE from positive to negative (P. Balaramet al., J. Am. Chem. Soc., 94, 4017 (1972); and A. A. Bothner-By et al.,Ann. N.Y. Acad. Sci. 222, 668 (1973)), or restricted diffusion (A. J.Lennon et al., Biophys., J. 67, 2096 (1994)) for the ligand. For themost part, these studies have focussed on protein/ligand systems wherethe small molecule was already known to be a ligand or was assumed to beone. In the last several years, however, the work of the Fesik (S. B.Shuker et al., Science , 274, 1531 (1996); and P. J. Hajduk et al., J.Am. Chem. Soc ., 119, 12257 (1997)), Meyer (B. Meyer et al., Eur. J.Biochem ., 246, 705 (1997)), Moore (J. Fejzo et al., Chem. Biol ., 6,755 (1999)), Shapiro (M. Lin et al., J. Org. Chem ., 62, 8930 (1997)),and Dalvit (C. Dalvit et al., J. Biomol NMR , 18, 65-68 (2000)) labs hasdemonstrated the applicability of these same general methods as ascreening tool to identify ligands from mixtures of small molecules.

These screening protocols typically involve the preparation of a seriesof individual samples in glass NMR tubes and the use of an autosamplerto achieve reasonable throughput. Variations in volume or positioningthat occur during sample preparation or tube insertion can necessitatetuning and calibration of the probe between each sample, therebyreducing throughput of data collection.

By contrast, flow-injection NMR has several advantages. The stationaryflow cell provides uniform locking and shimming from one sample to thenext, and, with the radio frequency coils mounted directly onto the flowcell's glass surface, high sensitivity. Fast throughput of datacollection is thus possible. Use of a liquid handler to prepare andinject samples, such as the Gilson 215 liquid handler used on Bruker andVarian systems, allows the potential for on-the-fly sample preparation(A. Ross et al., J. Biomol. NMR, 16, 139 (2000)), thus maximizing sampleintegrity and uniformity. Since the use and/or re-use of glass NMR tubesis avoided, costs are minimized.

Data Acquisition Hardware and Software

A typical Flow NMR system consists of a magnet, an NMR console, acomputer workstation, a Gilson sample handler, and a flow-injectionprobe. Two vendors currently offer complete flow-injection systems:Bruker Instruments and Varian Instruments. In addition, the NaloracCorporation manufactures an LC probe that can also be used forflow-injection NMR screening. A schematic of the Bruker EfficientTransport System (BEST) manufactured by Bruker Instruments is shown inFIG. 10. The Gilson 215 sample handler supplied by Bruker is equippedwith two Rheodyne 819 valves. The first valve is attached to a 5 mlsyringe, the needle capillary in the sample handler injection arm, thebridge capillary, the waste reservoir, and the second valve. The secondRheodyne valve is attached to the input and output of the probe, thesource of nitrogen gas, the first valve, and the injection port. FEPTeflon tubing is used in each of the connections with the exception ofthe gas connection, which uses PEEK tubing.

A sample is injected into the Bruker probe by filling the needlecapillary and transferring the sample into the inlet tubing for theprobe using the second Rheodyne valve. In quick mode, the next sample isloaded into the tubing during the spectral acquisition of the previoussample. When the spectral acquisition has completed, the first sampleexits the probe through the outlet capillary. This action pulls the nextsample into the probe through the inlet port and spectral acquisitioncan immediately begin. Quick mode acquisition can save approximately oneminute per sample from the time it would take to load each sampleindividually. However, sample recovery is not currently an option withthis method. In order to recover a sample, each sample is injectedindividually using normal mode acquisition. The sample is recovered byselecting either nitrogen gas or the syringe to pull the sample backfrom the probe through the inlet tube. The sample can then be returnedto the Gilson liquid handler into its original well or into a new 96well plate. A recovery unit has recently been added to the BEST systemto improve the efficiency of recovery of the syringe by using thenitrogen gas to create a back pressure on the sample.

Two useful accessories available for the BEST system are a Valvematesolvent switcher and a heated transfer line. The solvent switcher wasadded to the flow system for the combinatorial chemist who may want toanalyze samples in various organic solvents, but it can also be used fora library screen to vary buffer conditions or to clean the probe outwith an acid or a base. The heated transfer line is used to equilibratethe sample temperature to the probe temperature during sample transfer.Both the inlet and output capillary transfer lines are threaded throughthe heated transfer line. This feature is desirable when the spectralanalysis time is short and a high throughput of samples is required. Inthe ideal case, data acquisition using this accessory can beginimmediately after the sample enters the probe. Some samples may stillrequire a temperature equilibration period after entering the probe.

The setup of the Versatile Automated Sample Transport (VAST) systemproduced by Varian is similar to the Bruker system. The VAST systemconsists of a Gilson 215 liquid handler, a Varian NMR flow probe, an NMRconsole, and a Sun workstation. The Gilson liquid handler supplied byVarian is equipped with a single Rheodyne 819 valve and is connected tothe NMR flow probe with 0.010 inch inside diameter PEEK tubing (P. A.Keifer et al., J. Comb. Chem., 2, 151 (2000)). In the Varian systemdesign, the sample handler injects a specified volume of sample into theprobe, the data is acquired, and then the flow of liquid through thetubing is reversed and the sample is returned to its original vial orwell. The return of the sample to the Gilson by the syringe pump isassisted by a Valco valve and nitrogen gas which supply somebackpressure on the outlet portion of the Varian flow probe. With theVAST system setup, the probe is rinsed just prior to sample injectionand then is dried with nitrogen gas to minimize dilution of the sampleduring injection. The Varian design gives excellent sample recoverywithout dilution, but it is strongly recommended that samples befiltered to prevent clogging of the capillary transfer lines (P. A.Keifer et al., J. Comb. Chem., 2, 151 (2000)).

Flow NMR systems are ideally suited for use with the shielded magnetsmanufactured by Bruker Instruments or Oxford Magnets. Actively shieldinga 600 MHz magnet reduces the radial 5 gauss line from approximately 4meters to less than 2 meters, which allows the Gilson liquid handler tobe placed significantly closer to the magnet. This reduces the length oftubing needed between the Rheodyne valve and the flow-injection probeand minimizes the sample transfer time. The potential for clogging andsample dilution are concomitantly reduced.

Bruker uses two software packages to run the BEST system: BESTAdministrator and ICONNMR (Bruker Instruments, AMIX, BEST and ICONNMRsoftware packages). The BEST administrator is activated by typing thecommand ‘BESTADM’ in XWINNMR. This portion of the software is usedduring method generation and optimization. Samples are injected into theprobe one at a time and data is collected under XWINNMR. Early versionsof the BEST software utilized three separate programs: CFBEST, SUBEST,and OTBEST. These functions were recently combined under the singlesoftware package, BEST Administrator. In addition, the parametersavailable for customization have been greatly expanded to includeautomated solvent switching and method switching, which were notavailable in earlier versions of the software. The software packageICONNMR is used after a flow method has been optimized with the BESTadministrator. This package is setup for full automation and is the samesoftware used with automated NMR tube sample changers. In a similarfashion, Varian software uses the command ‘Gilson’ to generate a methodbefore sample injection and data acquisition is initiated usingEnter/Autogo in VNMR (Varian NMR Systems, VNMR software package).

Flow Probe Calibration and System Optimization

In addition to the normal 90° pulse lengths and power levels which arecalibrated for any NMR probe, several additional calibrations arerequired for a flow probe. The three additional volumes required tocalibrate a Bruker flow probe are shown schematically in FIG. 11 (BrukerInstruments, AMIX, BEST and ICONNMR software packages). The first volumecalibrated is the total probe volume. This can be accomplished byinjecting a colored liquid into the inlet of a dry probe with a syringeand watching for the liquid to appear in the outlet port (approximately700-800 μL for a 5 mm flow probe). With the Varian system, the systemfilling volume also includes the capillary tubing that connects theinjector port to the flow probe (P. A. Keifer et al., J. Comb. Chem., 2,151 (2000)). This volume is used to calculate the distance required toreposition a sample from the Gilson sample handler to the center of theflow cell in the probe.

The second volume calibrated is the flow cell volume. This is the volumeof liquid required to fully fill the coil around the flow cell. Thethree flow probe vendors (Bruker, Varian, and Nalorac) have probesavailable with active volumes ranging from 30-250 μL. The stated volumeof the flow cell in a 5 mm Bruker flow probe is 250 μL, but it wascalibrated to be approximately 300 μL. This volume can be calibrated bymaking repeated injections of a standard sample, starting with a volumeless than the stated active volume of the probe, and collecting a 1D ¹HNMR spectrum. The injection volume can then be increased incrementallyuntil no further improvement in signal-to-noise is observed.

In addition to the two probe volume calibrations already discussed,Bruker software also includes a third volume for calibration. Thisvolume, referred to as the positioning volume, is used to optimize thecentering of a sample in the flow cell. Early versions of ICONNMRsoftware (prior to 3.0.a.9) did not include the ability to set thepositioning volume. Rather, Bruker literature suggested that the flowcell volume should be roughly doubled to insure that the sample wouldcompletely fill the coil (Bruker Instruments, AMAX, BEST and ICONNMRsoftware packages). Fortunately, this is no longer necessary. Thepositioning volume can now be used to optimize the sample position. Thiscalibration reduced the sample size required for injection from 450 μLin the first few protein screens to 300 μL for current screens using aBruker 5 mm flow probe with an active volume of 250 μL. Optimization ofthis parameter minimized the sample volume required for each spectrum.Importantly, this significantly reduced the total amount of protein (orother target) at a given concentration needed to screen our smallmolecule library. The positioning volume can be optimized by collectinga series of spectra on a standard sample. In each spectrum collected,the positioning volume can first be varied by large increments (50-100μL) to get a rough estimate of the volume. An example of three suchspectra is shown in FIG. 12. The positioning volume can then be variedin smaller increments (10-25 μL) to identify the best volume for thisparameter. The best signal-to-noise was obtained for our 5 mm Brukerflow probe on a DRX-600 when the positioning volume was set to +25 μL,but this volume is probe specific and is calibrated for each flow probe.

The optimization of a flow-injection system for screening has three mainobjectives. The first objective is to transfer an aqueous sample to thecenter of the flow cell for analysis using the parameters determinedduring the flow probe calibration described above. The second objectiveis to reposition a sample from the Gilson liquid handler into theflow-injection probe without bubbles and with minimal sample dilution.This can be achieved by using nitrogen as a transfer gas (which keepsthe system under pressure) and by using a series of leading and trailingsolvents. In our experiments, we typically use 150 μL of ²H₂O as aleading solvent, 20 μL of nitrogen gas, 300 μL of sample, 20 μL ofnitrogen gas, and 100 μL of ²H₂O as a trailing solvent. Alternatively, alarger volume of sample can be used in place of the push solvents. Thethird objective is to determine a cleaning procedure which would reducesample carry-over to less than 0.1%. Typically, this involves rinsingthe probe with a predetermined volume of water. The rinse cycle can alsobe followed by a dry cycle, in which the capillary lines and flow probeare dried with nitrogen gas to further minimize sample dilution. In ourexperiments, we typically use a 1-mL wash volume followed by a 30 seconddrying time with nitrogen gas.

Design of Small Molecule Screening Libraries

With the increasing prevalence of extremely high throughput screeningequipment in the pharmaceutical industry, it may seem counter intuitiveto suggest screening smaller collections of compounds in an NMR-basedassay. However, a correlation between the quality of hits obtained andthe number of compounds screened has not been well documented. In fact,compounds are typically added to screening collections not to simplyincrease their numbers, but to increase the diversity and quality of thecompound collection. Thus, if one could find suitable hits from asmaller collection of well-chosen compounds, it may not be necessary toexpend the time and chemical resources to screen the entire compoundlibrary against every single target. Hits so identified could then beused to focus further screening efforts or to direct combinatorialsyntheses, thus saving both time and chemical resources, as shownschematically in FIG. 1. An NMR-based screen, like other binding assays,has the advantage in that a high throughput frictional assay does notneed to be developed. This will become increasingly important as moreand more targets of interest to pharmaceutical research are derived fromgenomics efforts and thus may not have a known function that can beassayed.

Several types of libraries are possible: broad screening librariesapplicable to many types of target proteins, directed libraries that aredesigned with the common features of an active site in mind that mightbe useful for screening a series of targets from the same protein class,such as protease enzymes, and “functional genomics” libraries composedof known substrates, cofactors and inhibitors for a diverse array ofenzymes that might be useful for defining the function ofgenomics-identified targets.

Ideally, the size and content of a broad screening library should besuch that screening can be accomplished in a day or two with a favorablechance of identifying several hits for each of the target proteins to bescreened. Rather than just randomly choosing a subset library, severalrationale approaches have been implemented. These include the SHAPESlibrary developed by Fejzo and coworkers that is composed largely ofmolecules that represent frameworks commonly found in known drugmolecules (J. Fejzo et al., Chem. Biol., 6, 755 (1999)), drug-like orlead-like libraries, and diversity-based libraries. A number of studieshave recently appeared that discuss the properties of known drugs andmethods to distinguish between drug-like and non-druglike compounds (G.W. Bemis et al., J. Med. Chem., 39, 2887 (1996); C. A. Lipinski et al.,Adv. Drug Del. Rev., 23, 3 (1997); Ajay et al., J. Med. Chem., 41, 3314(1998); J. Sadowski et al., J. Med. Chem., 41, 3325 (1998); A. K. Ghoseet al., J. Comb. Chem., 1, 55 (1999); J. Wang et al., J. Comb. Chem., 1,524 (1999); and G. W. Bemis et al., J. Med. Chem., 42, 5095 (1999)).Superimposing drug-like (E. J. Martin et al., J. Comb. Chem., 1, 32(1999)) or lead-like (S. J. Teague et al., Angew. Chem. Int. Ed., 38,3743 (1999)) properties on a diversity-selected compound set may yieldthe best library of compounds. The distinction of lead-like is importantsince the NMR-based assay is designed to identify weak-affinitycompounds that will most likely gain molecular weight and lipophilicityto become drug candidates or even lead chemical templates (S. J. Teagueet al., Angew. Chem. Int. Ed., 38, 3743 (1999)).

Development and expansion of our lead-like NMR screening library tomimic the structural diversity of our larger compound collection hasmade use of the DiverseSolutions software for chemical diversity (R. S.Pearlman et al., Persp. Drug Disc. Des., 9/10/11, 339 (1998)). In thisapproach, each compound is described by a set of descriptors, which aremetrics of chemistry space. Six orthogonal descriptors, related tosubstructures as opposed to the entire molecule, are often used. Whilethe descriptors to use can be automatically chosen to maximizediversity, typically there are two each corresponding to charge,polarizability and hydrogen-bonding. A cell-based diversity algorithm isemployed to divide the descriptor axes into bins and thus into a latticeof multidimensional hypercubes. As an example of how this can be used toconstruct or expand a small screening library, consider the selection of1,000 compounds from a compound library of 250,000 compounds. First, thecell-based algorithm is used to partition the 250,000 compounds intoapproximately 1,000 cells. The number of compounds per cell will varyand some will be empty. Maximum structural diversity will be obtained bytaking one compound from each occupied cell (and as close to the centeras possible). The actual compounds chosen are based on desirablelead-like properties such as low molecular weight and hydrophilicity aswell as availability and chemical non-reactivity as explained below.Diversity voids, as exemplified by empty cells, can be filled fromexternal sources or by chemical syntheses if desired. Identifying andfilling diversity voids is important since larger compound collectionsare often heavily weighted in certain classes of compounds stemming fromearlier research projects.

An example of diversity-based subset selection using these methods isshown in FIG. 13. Here, the 6,436 compounds from the ComprehensiveMedicinal Chemistry index have been divided into 2,012 cells to maximizediversity using five chemistry-space descriptors. The two-dimensionalrepresentation projected onto the hydrogen bond acceptor and charge BCUTaxes is shown in gray. The black squares correspond to the 1,474lead-like compounds (molecular weight less than 350 and 1<cLogP<3)contained in the CMC index. A total of 806 of the 2,012 cells wereoccupied by lead-like compounds. A similar approach could be used toselect diverse, lead-like compounds from a large corporate compoundcollection.

The cell concept of structural space is quite useful after the screeningis complete. When a hit is identified, other compounds from the same ornearby cells are obvious candidates for secondary assays. One can thinkof this as the gold mine analogy: when gold is struck, the search isbest continued in close proximity.

In addition to structural diversity, there are other characteristicsthat can be considered when selecting the subset molecules. Theseinclude purity, identity, reactivity, toxicological properties,molecular weight, water solubility, and suitability for chemicalelaboration by traditional or combinatorial methods. It makes sense topopulate the screening library with compounds of high integrity that arenot destined for failure down the road. Time spent upfront to insurepurity and identity with LC-MS or LC-NMR analyses will save resourcesdownstream. Filtering tools can be used to avoid compounds that areknown to be highly reactive, toxic, or to have poor metabolicproperties. Lack of reactivity is important since compounds can bescreened more efficiently as mixtures. Like other labs (S. B. Shuker etal, Science, 274, 1531 (1996); B. Meyer et al., Eur. J. Biochem., 246,705 (1997); J. Fejzo et al., Chem. Biol., 6, 755 (1999); and M. Lin etal., J. Org. Chem., 62, 8930 (1997)) we typically pool our selectedsmall molecules into mixtures of 6-10 compounds for screening (K. A.Farley et al., SMASH'99, Argonne, Ill., 15-18 August 1999).

Compounds chosen for our diversity library are lead-like as opposed todrug-like. It is often the case that chemical elaborations to improveaffinity also increase molecular weight and decrease solubility (S. J.Teague et al., Angew. Chem. Int. Ed., 38, 3743 (1999)). The molecularweight of the compounds therefore should preferably not exceed about350. Since most hits obtained will have affinities for their target inthe approximately 100 μM range, low molecular weight will leave room forchemical elaboration to build in more affinity and selectivity. Usinglarger molecular weight drug-like compounds would not substantiallyimprove affinity of the hits and could easily preclude obtaining leadchemical templates of reasonable size. Lead-like hits that arereasonably water soluble allow for chemical elaboration that results inmodest increased lipophilicity of the final therapeutic entity (S. J.Teague et al., Angew. Chem. Int. Ed., 38, 3743 (1999)). Water solubilityis also important since it enhances the potential success of downstreamstudies such as calorimetry, enzymology, cocrystallization and NMRstructural studies. Compound solubility is especially important forflow-injection NMR methods in order to prevent clogging of the capillarylines.

Compounds should also be chosen with their suitability for chemicalelaboration by traditional or combinatorial chemistry methods in mind.Hits with facile handles for synthetic chemistry will be of moreinterest and will allow more efficient use of often limited medicinalchemistry resources.

Relaxation-Edited or WaterLOGSY-Based Flow-Injection NMR ScreeningMethods

Calibration and validation of the flow system and creation of asmallmolecule screening library yields an automated system that is readyto screen new targets. A protein target can be analyzed forprotein-ligand interactions using relaxation-editing methods by addingsufficient protein to each well of the 96-well library plate to give a1:1 (protein:ligand) ratio at a concentration of approximately 50 μM.Homogeneous sample dispersion throughout the well can be facilitated byagitating the plate on a flat bed shaker. Screening at thisconcentration allows a decent 1D ¹H NMR spectrum to be acquired in about10 minutes. In our experience, this concentration of target and smallmolecule requires identified ligands to have affinities on the order ofapproximately 200 μM or tighter.

Once the screening plate has been prepared, the Gilson liquid samplehandler transfers samples from 96-well plates into the flow-injectionprobe and if desired, returns the samples back into either the original96-well plate or a new plate. Once the sample is in the magnet, spectrathat can detect changes in chemical shifts, relaxation properties, ordiffusion properties can be collected. In our relaxation-edited NMRscreening assay, two 1D relaxation-edited ¹H NMR spectra are collected:one spectrum is collected on the ligand mixture in the presence ofprotein and the second, control spectrum is collected on the ligandmixture in the absence of protein. Ligands are identified as binding toa target when their resonances are greatly reduced when compared to arelaxation-edited spectrum collected in the absence of protein asillustrated in FIG. 14. In this example, the target protein was agenomics-derived protein of unknown function.

Ligand binding can be confirmed by collecting a 1D relaxation-edited ¹HNMR spectrum of each individual ligand that was identified as binding tothe protein in a given mixture as shown in FIG. 15. In addition, thebinding. constant of the protein/ligand interaction can be estimatedusing 1D diffusionedited spectra of the ligand in the presence andabsence of protein (A. J. Lennon et al., Biophys. J., 67, 2096 (1994)).If labeled protein is available, a 2D ¹H-¹⁵N HSQC spectrum can also beobtained to locate the ligand binding site on the protein (J. Wang etal., Biochemistry, 31, 921 (1992); and S. B. Shuker et al, Science, 274,1531 (1996)). In cases where the protein is small enough and structuralcharacterization of the binding interaction is desired, furtherexperiments can be carried out using ¹⁵N and/or ¹³C/¹⁵N protein/ligandcomplexes.

When binding is detected using the WaterLOGSY technique, samplepreparation and use of the flow-injection apparatus is identical, exceptthat extremely low levels of target are used (1-10 μM) with ratios ofligand to target of 100:1 to 10:1. For data analysis, binding compoundsare distinguished from nonbinders by the opposite sign of theirwater-ligand NOEs. In contrast to the relaxation-edited technique, onlya single WaterLOGSY spectrum is used for each ligand mixture. There isno need to collect a reference spectrum in the absence of targetprotein. An example is illustrated in FIG. 16 for a mixture of compoundsand a different protein. In the WaterLOGSY spectrum shown in FIG. 16,binding compounds have resonances of opposite intensity (sharp positivepeaks) than nonbinders (near zero intensity or sharp negative peaks).Residual protein resonances are also of positive intensity.

Data Analysis

The development of flow probes has facilitated the transition tohigh-throughput NMR and has made possible the routine collection oftremendous volumes of data. Recent software developments have advancedthe automated handling of large data sets collected on combinatorialchemistry libraries (P. A. Keifer et al., J. Comb. Chem., 2, 151 (2000);Bruker Instruments, AMIX, BEST and ICONNMR software packages; Varian NMRSystems, VNMR software package; and Williams A, Book of Abstracts, 218thACS National Meeting (1999)). Visualization of results in a 96-wellformat allows rapid evaluation of the data sets. The integration offeatures such as this into a software package tailored more for datareduction and evaluation of library screening data sets parallels thecombinatorial chemistry software development but remains slightlybehind. However, recent advancements that have been made forcombinatorial chemistry data analyses portend similar developments forthe automation of protein binding screening data.

In our 1D relaxation-edited ¹H NMR data sets, one can simply identifythe ligand resonances by inspection since their intensity is reduced inthe presence of protein as shown in FIG. 14. In our WaterLOGSY datasets, binding compounds are distinguished from nonbinders by theopposite sign of their water-ligand NOEs as observed in FIG. 15. Ineither case, comparison to an assigned small molecule control spectrumare made to identify the compound associated with the indicatedresonances.

Other labs have relied on difference spectra to analyze relaxation- ordiffusing-edited 1D ¹H NMR data sets (P. J. Hajduk et al., J. Am. Chem.Soc., 119, 12257 (1997); N. Gonnella et al., J. Magn. Reson., 131, 336(1998); and A. Chen et al., J. Am. Chem. Soc., 122, 414 (2000)). After aseries of spectral subtractions, the resulting spectrum represents theresonances of the compounds that bind to the protein. Two factors thatpose problems are line broadening and shifting resonances, both of whichcan lead to subtraction artifacts. Changes in intensity can also add theneed for a scaling factor in the data analysis step. These additionalsteps, which can vary from one spectra to the next, make strategies forautomated data analysis complex.

Data analysis for 2D screening methods typically involves either theanalysis of protein chemical shift perturbations indicative of ligandbinding (A. Ross et al., J. Biomol. NMR, 16, 139 (2000); and S. B.Shuker et al, Science, 274, 1531 (1996)), or the analysis of changes insignals from the small molecules in NOE or DECODES spectra indicative ofbinding (B. Meyer et al., Eur. J. Biochem., 246, 705 (1997); J. Fejzo etal., Chem. Biol., 6, 755 (1999); and M. Lin et al., J. Am. Chem. Soc.,119, 5249 (1997)). While a series of 2D ¹H-¹⁵N HSQC spectra can becompared manually, automated analysis using both non-statistical andstatistical approaches of a series of ¹H-¹⁵N HSQC spectra acquired withflow-injection NMR methods was recently demonstrated (A. Ross et al., J.Biomol. NMR, 16, 139 (2000)). AMIX was used for the non-statisticalanalysis by comparing spectra collected in the presence of singlecompounds to the reference spectrum of the protein alone. Then, usingbucketing calculations for data reduction, a table ranked by thecorrelation coefficient was generated. No correlations were observedusing the bucketing calculations alone. Subsequently, integrationpatterns for all 300 small molecule spectra were analyzed by AMIX togenerate a data matrix of N integration regions times 300. A statisticalsoftware package, UNSCRAMBLER 6.0, was then used to analyze this datamatrix using principal components analysis. Two classes of spectralchanges were observed. Ultimately, one class was found to correspond topH changes caused by certain small molecules while the other classcorresponded to small molecules binding to the target protein (A. Rosset al., J. Biomol. NMR, 16, 139 (2000)).

Data reduction is an important aspect for handling the amounts of datagenerated if high-throughput screening by NMR is to be successful.Non-statistical methods such as the bucketing calculations of AMIX(Bruker Instruments, AMIX, BEST and ICONNMR software packages) or thedatabase comparisons of ACD (Williams A, Book of Abstracts, 218th ACSNational Meeting (1999)) compare chemical shift, multiplicity,integration regions and patterns to give correlation factors betweenspectra. These software packages can be used for data reduction of bothone- and two-dimensional data. Prediction software is also available tohelp aid in interpretation of data sets. Statistical methods such asprincipal components analysis can be used to analyze data for othercorrelations that are not apparent using non-statistical methods alone.In the case of 2D ¹H-¹⁵N HSQC data, an adaptive, multivariate methodthat incorporates a weighted mapping of perturbations to correlateinformation within a spectrum or across many spectra has also beendescribed (F. Delaglio, CHI Conference on NMR Technologies: Developmentand Applications for Drug Discovery, Baltimore, Md., 4-5 Nov. 1999).

Comparison of Flow vs. Traditional Methods

The advantage of working with samples in the flow NMR screeningenvironment is that each set of spectra are collected on samples thatare at the same concentration. This accelerates spectral acquisitionconsiderably. Since the samples are fairly homogenous, many of theroutine tasks need to be completed on only the first sample: probetuning, ¹H 90° pulse calibration, receiver gain, number of transients,locking, and gradient shimming. On subsequent samples, these steps canbe omitted, although simplex shimming of Z₁ and Z₂ can still be usedwith multi-day acquisitions.

Prerequisites for a high-throughput assay include rapid data collection,sample-to-sample integrity and minimal costs. Flow NMR techniques havebeen developed with each in mind. For 1D ¹H NMR screening experiments,the process of removing the previous sample from the flow cell, rinsingthe flow cell, injecting the next sample, allowing for thermalequilibration, automating solvent suppression and acquiring the data cantake less than 10 minutes. In practice, the use of this procedure is twoto three times faster than a sample changer with conventional NMR tubes.If compounds were screened in mixtures of 10, this results in athroughput of about 1,500 compounds per day. Use of a liquid handler,such as the Gilson 215 typically employed by Bruker and Varian flow NMRsystems, can simplify the preparation of samples as well. Ross andcoworkers have demonstrated on-the-fly sample preparation by using theliquid handler to mix the protein to be screened with the small moleculeimmediately prior to injection (A. Ross et al., J. Biomol. NMR, 16, 139(2000)). Sample conditions can thus be highly standardized with theresulting spectra very consistent and reproducible. Even if targetprotein is added manually to pre-plated screening libraries, the amountof pipetting is still less than if using NMR tubes. Recurring expensesassociated with purchasing and/or cleaning NMR tubes are eliminated withflow-injection NMR methods. The cost of the 96-well microtitre plates isinsignificant compared to NMR tubes.

The complete disclosures of the patents, patent documents, andpublications cited herein are incorporated by reference in theirentirety as if each were individually incorporated. Variousmodifications and alterations to this invention will become apparent tothose skilled in the art without departing from the scope and spirit ofthis invention. It should be understood that this invention is notintended to be unduly limited by the illustrative embodiments andexamples set forth herein. Such examples and embodiments are presentedby way of example only with the scope of the invention intended to belimited only by the claims set forth herein as follows.

1. A method of identifying a compound that binds to a target molecule,the method comprising: selecting a library comprising test compounds,wherein each test compound is selected based on having a solubility indeuterated water of at least about 1 mM at room temperature and amolecular weight of no greater than about 350 grams/mole; providing aplurality of mixtures of the test compounds, each mixture being in asample reservoir; introducing a target molecule into each of the samplereservoirs to provide a plurality of test samples; providing a nuclearmagnetic resonance spectrometer equipped with a flow-injection probe;transferring each test sample from the sample reservoir into theflow-injection probe; collecting a relaxation-edited nuclear magneticresonance spectrum on each test sample in each sample reservoir; andcomparing the spectra of each test sample to the spectra taken under thesame conditions in the absence of the target molecule to identify testcompounds that bind to the target molecule; wherein the concentration oftarget molecule and each test compound in each sample reservoir is nogreater than about 100 μM; and wherein the ratio of target molecule toeach test compound in each sample reservoir is about 1:1.
 2. The methodof claim 1 wherein each mixture is in a sample reservoir of a multiwellsample holder.
 3. The method of claim 2 wherein the multiwell sampleholder is a 96-well microtiter plate.
 4. The method of claim 1 whereincollecting a relaxation-edited nuclear magnetic resonance spectrumcomprises collecting a 1D relaxation-edited nuclear magnetic resonancespectrum.
 5. The method of claim 4 wherein collecting a 1Drelaxation-edited nuclear magnetic resonance spectrum comprisescollecting a 1D relaxation-edited ¹ H nuclear magnetic resonancespectrum.
 6. The method of claim 1 wherein the mixture of test compoundscomprises at least about 3 compounds, each having at least onedistinguishable resonance in a 1D NMR spectrum of the mixture.
 7. Themethod of claim 6 wherein the mixture of test compounds comprises atleast about 6 compounds.
 8. The method of claim 1 wherein theconcentration of target molecule and each test compound in each samplereservoir is no greater than about 50 μM.
 9. The method of claim 1further wherein comparing spectra to identify test compounds that bindto the target molecule comprises identifying a test compound that bindsto the target molecule with a dissociation constant at least about 100μM.
 10. The method of claim 1 wherein the target molecule is a protein.11. The method of claim 1 wherein the library comprises at least 75 andno more than about 10,000 test compounds.
 12. The method of claim 11wherein the library comprises at least 300 compounds.
 13. The method ofclaim 11 wherein the library comprises at least 2000 compounds.
 14. Amethod of identifying a compound that binds to a target molecule, themethod comprising: selecting a library comprising at least 75 and nomore than about 10,000 test compounds, wherein each test compound has asolubility in deuterated water of at least about 1 mM at roomtemperature, and has a molecular weight of no greater than about 350grams/mole; providing a plurality of mixtures of the test compounds,each mixture being in a sample reservoir; introducing a target moleculeinto each of the sample reservoirs to provide a plurality of testsamples; providing a nuclear magnetic resonance spectrometer equippedwith a flow-injection probe; transferring each test sample from thesample reservoir into the flow-injection probe; collecting arelaxation-edited nuclear magnetic resonance spectrum on each testsample in each sample reservoir, and comparing the spectra of each testsample to the spectra taken under the same conditions in the absence ofthe target molecule to identify test compounds that bind to the targetmolecule; wherein the concentration of target molecule and each testcompound in each sample reservoir is no greater than about 100 μM; andwherein the ratio of target molecule to each test compound in eachsample reservoir is about 1:1.
 15. The method of claim 14 wherein thelibrary comprises at least 300 compounds.
 16. The method of claim 14wherein the library comprises at least 2000 compounds.